Downloads · 30 days
4
19% of all-time downloads
ASAP_FineTuningBERT_AugV8_k2_task1_organization_fold4
genki10/ASAP_FineTuningBERT_AugV8_k2_task1_organization_fold4
ASAP_FineTuningBERT_AugV8_k2_task1_organization_fold4 is a text classification model from genki10. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
All-time downloads
21
Public
Parameters
109M
876 MB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors438 MB · 100%
At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- Feb 3, 2025
- Updated
- Feb 3, 2025
- SHA
- 71d9478d
Try a prompt
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
ASAP_FineTuningBERT_AugV8_k2_task1_organization_fold4
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.1154
- Qwk: 0.3930
- Mse: 1.1154
- Rmse: 1.0561
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 100
Training results
| Training Loss | Epoch | Step | Validation Loss | Qwk | Mse | Rmse |
|---|---|---|---|---|---|---|
| No log | 1.0 | 2 | 10.3681 | 0.0037 | 10.3681 | 3.2200 |
| No log | 2.0 | 4 | 9.8337 | 0.0018 | 9.8337 | 3.1359 |
| No log | 3.0 | 6 | 9.2950 | 0.0018 | 9.2950 | 3.0488 |
| No log | 4.0 | 8 | 7.6364 | 0.0018 | 7.6364 | 2.7634 |
| 7.4321 | 5.0 | 10 | 6.3080 | 0.0 | 6.3080 | 2.5116 |
| 7.4321 | 6.0 | 12 | 5.3098 | 0.0222 | 5.3098 | 2.3043 |
| 7.4321 | 7.0 | 14 | 4.2319 | 0.0079 | 4.2319 | 2.0572 |
| 7.4321 | 8.0 | 16 | 3.2295 | 0.0079 | 3.2295 | 1.7971 |
| 7.4321 | 9.0 | 18 | 2.2769 | 0.1339 | 2.2769 | 1.5090 |
| 3.4188 | 10.0 | 20 | 1.5508 | 0.0445 | 1.5508 | 1.2453 |
| 3.4188 | 11.0 | 22 | 1.3006 | 0.0445 | 1.3006 | 1.1404 |
| 3.4188 | 12.0 | 24 | 1.1983 | 0.0495 | 1.1983 | 1.0947 |
| 3.4188 | 13.0 | 26 | 1.0830 | 0.0658 | 1.0830 | 1.0407 |
| 3.4188 | 14.0 | 28 | 1.3415 | 0.1436 | 1.3415 | 1.1582 |
| 1.9137 | 15.0 | 30 | 1.2975 | 0.1737 | 1.2975 | 1.1391 |
| 1.9137 | 16.0 | 32 | 1.1237 | 0.2462 | 1.1237 | 1.0601 |
| 1.9137 | 17.0 | 34 | 1.3118 | 0.2460 | 1.3118 | 1.1453 |
| 1.9137 | 18.0 | 36 | 1.0005 | 0.3452 | 1.0005 | 1.0003 |
| 1.9137 | 19.0 | 38 | 1.2575 | 0.3204 | 1.2575 | 1.1214 |
| 1.2854 | 20.0 | 40 | 0.8810 | 0.4113 | 0.8810 | 0.9386 |
| 1.2854 | 21.0 | 42 | 1.1965 | 0.3539 | 1.1965 | 1.0938 |
| 1.2854 | 22.0 | 44 | 0.8713 | 0.4240 | 0.8713 | 0.9334 |
| 1.2854 | 23.0 | 46 | 0.7629 | 0.4951 | 0.7629 | 0.8734 |
| 1.2854 | 24.0 | 48 | 1.0313 | 0.3921 | 1.0313 | 1.0155 |
| 0.6102 | 25.0 | 50 | 0.8027 | 0.4927 | 0.8027 | 0.8959 |
| 0.6102 | 26.0 | 52 | 1.1482 | 0.4121 | 1.1482 | 1.0715 |
| 0.6102 | 27.0 | 54 | 0.8849 | 0.4771 | 0.8849 | 0.9407 |
| 0.6102 | 28.0 | 56 | 1.0759 | 0.4125 | 1.0759 | 1.0373 |
| 0.6102 | 29.0 | 58 | 0.9356 | 0.4478 | 0.9356 | 0.9673 |
| 0.3083 | 30.0 | 60 | 1.1359 | 0.4229 | 1.1359 | 1.0658 |
| 0.3083 | 31.0 | 62 | 1.1750 | 0.4118 | 1.1750 | 1.0840 |
| 0.3083 | 32.0 | 64 | 1.1024 | 0.4296 | 1.1024 | 1.0500 |
| 0.3083 | 33.0 | 66 | 1.1154 | 0.3930 | 1.1154 | 1.0561 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Feb 3, 2025
- Updated
- Feb 3, 2025